About me

I am a PostDoc at UC Berkeley, working with Prof. Dawn Song. I obtained my PhD degree at the Department of Computer Science at ETH Zurich. I was part of the Secure, Reliable, and Intelligent Systems Lab supervised by Prof. Martin Vechev. My research focuses on security and machine learning.

Publications

2024

Exploiting LLM Quantization
Kazuki Egashira, Mark Vero, Robin Staab, Jingxuan He, Martin Vechev
NeurIPS 2024 NextGenAISafety@ICML24 Oral
SWT-Bench: Testing and Validating Real-World Bug-Fixes with Code Agents
Niels Mündler, Mark Niklas Müller, Jingxuan He, Martin Vechev
NeurIPS 2024
Practical Attacks against Black-box Code Completion Engines
Slobodan Jenko, Jingxuan He, Niels Mündler, Mark Vero, Martin Vechev
arXiv 2024
Instruction Tuning for Secure Code Generation
Jingxuan He*, Mark Vero*, Gabriela Krasnopolska, Martin Vechev
ICML 2024 * Equal contribution

2023

Large Language Models for Code: Security Hardening and Adversarial Testing
Jingxuan He, Martin Vechev
ACM CCS 2023 Distinguished Paper Award

2022

On Distribution Shift in Learning-based Bug Detectors
Jingxuan He, Luca Beurer-Kellner, Martin Vechev
ICML 2022

2021

Learning to Explore Paths for Symbolic Execution
Jingxuan He, Gishor Sivanrupan, Petar Tsankov, Martin Vechev
ACM CCS 2021
TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer
Berkay Berabi, Jingxuan He, Veselin Raychev, Martin Vechev
ICML 2021
Learning to Find Naming Issues with Big Code and Small Supervision
Jingxuan He, Cheng-Chun Lee, Veselin Raychev, Martin Vechev
PLDI 2021

2020

Learning Fast and Precise Numerical Analysis
Jingxuan He, Gagandeep Singh, Markus Püschel, Martin Vechev
PLDI 2020

2019

Learning to Fuzz from Symbolic Execution with Application to Smart Contracts
Jingxuan He, Mislav Balunović, Nodar Ambroladze, Petar Tsankov, Martin Vechev
ACM CCS 2019

2018

DEBIN: Predicting Debug Information in Stripped Binaries
Jingxuan He, Pesho Ivanov, Petar Tsankov, Veselin Raychev, Martin Vechev
ACM CCS 2018